Sensai “High End Data Science at Radical Price Point”

Tuesday, 31/03/2015 | 17:09 GMT by Ron Finberg
  • Aiming to be “Palantir for everyone else, a high-end data science platform delivered at a radical price point", Sensai launches today
Sensai “High End Data Science at Radical Price Point”

Publicly launching today is Sensai, a new data science platform “for the unstructured world”. Providing services for multiple industries, already within its ‘stealth mode’, Sensai has attracted interest from the financial firms such as UBS and WorldQuant that had been early users of their product.

As ‘Big Data ’ has expanded to become an essential component in the financial field to monitor risk, perform real time asset valuations, and forecast the market, data science demands have moved from handling structured to unstructured data. With structured data, software is built to run queries based using tabular formed data. The advantage of structured data is that new information can be quickly indexed to analyze and perform historical reports and future forecasts. However, calculations are limited to the specific data types.

With unstructured data science, analysts integrate information that is difficult to index into structured datasets. Examples are regulatory filings, news reports, and social buzz, which could include the emergence or increased frequency of specific words that indicate a potentially impactful event coming to the financial markets.

Sensai aims to be “Palantir for everyone else, a high-end data science platform delivered at a radical price point.”

Providing a solution, Sensai provides tools for data science teams to perform their own analysis of unstructured data, thus automating analysis functions that are very often conducted manually. By targeting the financial industry, Sensai becomes one of many startups and multi-billion firms competing in the big data market.

Aiming to distinguish itself, Sensai is pricing its solution at a level that will make their product appealing to a wider audience than existing services in the financial market. Explained to Forex Magnates by a Sensai representative, the firm aims to be “Palantir for everyone else, a high-end data science platform delivered at a radical price point.”

Sensai’s launch occurs as the firm graduated from the Data Elite incubator as well as raising $900,000 in seed funding from investors including Andreessen Horowitz, Formation8, and ValueStream Labs.

Jonas Lamis, CEO and co­founder of Sensai

Jonas Lamis, CEO and co­founder of Sensai

In their public statement about the launch today, Jonas Lamis, CEO and co­founder of Sensai said “The world’s largest businesses have been forced to make decisions without the insights they need from unstructured data that has been available to them for years. With the launch of Sensai, we’re putting the most advanced tools for analysis of unstructured data in the hands of data science teams. Our customers now have the ability to stay ahead of their market and make better decisions without investing in massive initiatives that rely upon slow, costly and custom­built processes.”

Publicly launching today is Sensai, a new data science platform “for the unstructured world”. Providing services for multiple industries, already within its ‘stealth mode’, Sensai has attracted interest from the financial firms such as UBS and WorldQuant that had been early users of their product.

As ‘Big Data ’ has expanded to become an essential component in the financial field to monitor risk, perform real time asset valuations, and forecast the market, data science demands have moved from handling structured to unstructured data. With structured data, software is built to run queries based using tabular formed data. The advantage of structured data is that new information can be quickly indexed to analyze and perform historical reports and future forecasts. However, calculations are limited to the specific data types.

With unstructured data science, analysts integrate information that is difficult to index into structured datasets. Examples are regulatory filings, news reports, and social buzz, which could include the emergence or increased frequency of specific words that indicate a potentially impactful event coming to the financial markets.

Sensai aims to be “Palantir for everyone else, a high-end data science platform delivered at a radical price point.”

Providing a solution, Sensai provides tools for data science teams to perform their own analysis of unstructured data, thus automating analysis functions that are very often conducted manually. By targeting the financial industry, Sensai becomes one of many startups and multi-billion firms competing in the big data market.

Aiming to distinguish itself, Sensai is pricing its solution at a level that will make their product appealing to a wider audience than existing services in the financial market. Explained to Forex Magnates by a Sensai representative, the firm aims to be “Palantir for everyone else, a high-end data science platform delivered at a radical price point.”

Sensai’s launch occurs as the firm graduated from the Data Elite incubator as well as raising $900,000 in seed funding from investors including Andreessen Horowitz, Formation8, and ValueStream Labs.

Jonas Lamis, CEO and co­founder of Sensai

Jonas Lamis, CEO and co­founder of Sensai

In their public statement about the launch today, Jonas Lamis, CEO and co­founder of Sensai said “The world’s largest businesses have been forced to make decisions without the insights they need from unstructured data that has been available to them for years. With the launch of Sensai, we’re putting the most advanced tools for analysis of unstructured data in the hands of data science teams. Our customers now have the ability to stay ahead of their market and make better decisions without investing in massive initiatives that rely upon slow, costly and custom­built processes.”

About the Author: Ron Finberg
Ron Finberg
  • 1983 Articles
  • 8 Followers
About the Author: Ron Finberg
Ron Finberg, a specialist in regulatory issues, brings clarity and depth to finance news
  • 1983 Articles
  • 8 Followers

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